1. Field of the Invention
This disclosure relates to the field of machine vision, which may be useful in robotics, inspection or modeling.
2. Description of the Related Art
Increasingly more manufacturing operations are performed with the aid of industrial robots. Robots that had traditionally been used as blind motion playback machines are now benefiting from intelligent sensor-based software to adapt to changes in their surroundings. In particular, the use of machine vision has been on the rise in industrial robotics. A typical vision guided robotic system analyzes image(s) from one or more cameras to arrive at such information as the position and orientation of a workpiece upon which the robotic tool is to operate.
Early implementations of vision guided robots have provided only limited part pose information, primarily in the two-dimensional space whereby the movement of a given part is constrained to a planar surface. For example see U.S. Pat. No. 4,437,114 LaRussa. However, many robotic applications require the robot to locate and manipulate the target workpiece in three dimensions. This need has sparked many attempts at providing various three-dimensional guidance capabilities. In many past cases, this has involved using two or more cameras that view overlapping regions of the object of interest in what is known as a stereo configuration. The overlapping images or fields-of-view contain many of the same object features viewed from two or more vantage points. The difference amongst the apparent position of corresponding features in each of the images i.e., the parallax, is exploited by these methods to calculate the three dimensional coordinates of such features. For examples see U.S. Pat. No. 4,146,924 Birk et al., and U.S. Pat. No. 5,959,425 Bieman et al.
Many drawbacks exist that render stereo based systems impractical for industrial applications. The measurement error in such systems increases rapidly in response to image feature detection errors; these systems also require exactly known geometrical relationships between camera pairs. Furthermore stereo methods require the use of at least double the number of cameras which drives up the cost, complexity and the need for calibration.
Other attempts at locating objects with multiple cameras in the past have taken advantage of video cameras in combination with laser light projectors that project various stationary or moving patterns such as stripes, cross-hairs and the like upon the object of interest. These systems typically involve a combination of lasers and cameras that must be calibrated relative to a common coordinate system and rely on specific assumptions about the geometry of the object of interest to work. For example see U.S. Pat. No. 5,160,977 Utsumi.
Drawbacks of such attempts include the need for expensive specialized sensors as opposed to use of standard off-the-shelf hardware, the need for knowledge of exact geometric relationships between all elements of the system including cameras and lasers, susceptibility to damage or misalignment when operating in industrial environments as well as posing of a potential safety hazard when laser light sources are deployed in proximity of human operators.
Based on the above considerations it is desirable to devise a three-dimensional robot guidance system that eliminates the need for stereo camera pairs and the need for the use of structured light and specialized sensors. Such a system would increase accuracy, simplify setup and maintenance and reduce hardware costs.
Prior methods have been developed that utilize a single camera to view each region/feature of the object in order to calculate the 3D pose of the object. For example see U.S. Pat. No. 4,942,539 McGee, and European Patent No. 0911603B1 Ersu. However these and similar methods require the calibration of all cameras relative to a common coordinate frame such as a robot. In practice such a requirement is cumbersome and time-consuming to fulfill and difficult to automate. These methods also require a priori knowledge of the geometrical relationships between all object features used. One source for such data is object Computer Aided Design (CAD) models; however, such data files are often not readily available. In the absence of CAD data, past systems have relied on direct object measurement using a coordinate measurement machine or a robot equipped with a pointing device. This process is difficult and error prone especially in the case of large objects with features that are scattered in different regions.
It is therefore highly desirable to develop a three-dimensional robot guidance system that in addition to eliminating the need for stereo cameras and lasers, also eliminates the need for inter-camera calibration and the need for a priori knowledge of geometrical relationships between all object features.